Adventures in Data Visualization: Lessons Learned and Applied

Concurrent Session 3
Streamed Session

Watch This Session

Session Materials

Brief Abstract

In this session, the facilitator shares lessons learned about data visualization and how her research unit has applied what they have learned to a range of projects. Participants will leave the session with a set of resources for their own professional development as well as a practical data visualization roadmap.


Dr. Katie Linder is an avid writer and researcher with a passion for process and peeking behind the scenes at what it takes to be a successful academic. Currently, Katie directs the Oregon State University Ecampus Research Unit and serves as an associate editor for the International Journal for Academic Development. She is also the creator of the Radical Self-Trust Podcast Channel and the host of a weekly interview-based podcast called Research in Action. She writes a weekly essay series called The Academic Creative. Her most recent book is Managing Your Professional Identity Online: A Guide for Faculty, Staff, and Administrators.

Extended Abstract

As the data landscape is expands, effective data visualization is becoming a key competency for online teaching and learning administrators wishing to communicate value and results to key stakeholders. However, many administrators are not trained in data visualization best practices.

In this session, the presenter shares her experience of a self-study of data visualization undertaken by her online education research unit and offers examples of how her research unit has applied what they have learned to a range of projects.

In particular, she shares 10 lessons learned regarding:

1. Data visualization as storytelling
2. Shaping data visualization for different audiences
3. How to choose the right chart or graph to fit your data
4. The importance of color
5. The role of font choice
6. The impact of institutional branding on data visualizations
7. Embedding accessibility into data vizualizations
8. Repurposing data visualizations
9. Learning from data visualizations "in the wild" and
10. How to approach a self-study of data visualization

In the beginning of the session, participants will be asked to share what they know about best practices for data visualizations through a think-pair-share activity.

Throughout the session, the facilitator will share a range of before-and-after examples of data visualizations. Participants will be asked to try and identity the weaknesses and strengths of each pairing using information provided throughout the session.

At the end of the session, participants will complete a data visualization roadmap where they will answer reflective and practical questions to choose a data visualization method to apply to one of their own projects.

Participants who attend this session will be able to:
1. Recognize examples of effective data visualization
2. Identify data visualization best practices
3. Participants will be able to apply a data visualization roadmap to their own projects